flint.sky_model

Attributes

KNOWN_1934_FILES	Known models of PKS B1934-638 in different formats
KNOWN_CATAS	Known sky-model catalogues that have had some pre-processing operations applied. Discuss with maintainers for access,
KNOWN_PB_TYPES
NORM_COLS	Normalised column names and their corresponding astropy units.

Classes

AiryResponse	Container describing a airy disc response
CurvedPL	Container for results of a Curved Power Law,
GaussianResponse	Container describing a simple Gaussian taper
SincSquaredResponse	Container describing a sinc-squared response
SkyModel	Description of the derived sky-model
SkyModelOptions	Options that describe how to build a local sky-model, including
SkyModelOutputPaths	Holds the expected names for different type of sky model outputs

Functions

_jinc(x)
cli(→ None)
create_sky_model(→ SkyModel | None)	Create a sky-model to calibrate RACS based measurement sets.
curved_power_law(→ numpy.ndarray)	A curved power law model.
evaluate_src_model(→ astropy.units.Jy)	Evaluate a SED of an object using its recordded
fit_curved_pl(→ CurvedPL)	Fit some specified set of datapoints with a generic
generate_airy_pb(→ AiryResponse)	Calculate the theoretical airy response of an aperture of
generate_gaussian_pb(→ GaussianResponse)	Calculate the theoretical Gaussian taper for an aperture of
generate_pb(...)	Generate the primary beam response using a set of physical quantities. Each
generate_sinc_squared_pb(→ SincSquaredResponse)	Calculate the theoretical sinc-squared response of an aperture of
get_1934_model(→ pathlib.Path)	Construct the path to a 1934-638 model. This is intended to calibrate
get_known_catalogue(→ flint.catalogue.Catalogue)	Get the parameters of a known catalogue
get_parser()
get_sky_model_output_paths(→ SkyModelOutputPaths)	Create a set of expected sky model output file paths
load_catalogue(→ tuple[flint.catalogue.Catalogue, ...)	Load in a catalogue table given a name or measurement set declinattion.
make_calibrate_model(→ pathlib.Path)	Create a sky-model file that is compatible with the AO Calibrate software
make_ds9_region(→ pathlib.Path)	Create a DS9 region file of the sky-model derived
make_hyperdrive_model(→ pathlib.Path)	Writes a Hyperdrive sky-model to a yaml file.
preprocess_catalogue(→ astropy.table.QTable)	Apply the flux and separation cuts to a loaded table, and transform input column names to an

Module Contents

class flint.sky_model.AiryResponse

Bases: NamedTuple

Container describing a airy disc response

atten: numpy.ndarray

The attenuation of the response

freqs: numpy.ndarray

The frequencies the beam is evaluated at

fwhms: numpy.ndarray

The full-width at half-maximum corresponding to freqs

offset: float

Angular offset of the source

class flint.sky_model.CurvedPL

Bases: NamedTuple

Container for results of a Curved Power Law,

>>> S_nu = S_nu_0 * (nu/nu_0)**alpha * exp(q*ln(nu/nu_0)**2.)

Note that in the case of q=0. the model reduces to a normal power-law.

alpha: float

The fitted spectral index

norm: float

The fitted normalisation of the fitted model

q: float

The fitted curvature of the spectral index

ref_nu: float

The nominated reference frequency

class flint.sky_model.GaussianResponse

Bases: NamedTuple

Container describing a simple Gaussian taper

atten: numpy.ndarray

The attenuation of the response

freqs: numpy.ndarray

The frequencies the beam is evaluated at

fwhms: numpy.ndarray

The full-width at half-maximum corresponding to freqs

offset: float

Angular offset of the source

class flint.sky_model.SincSquaredResponse

Bases: NamedTuple

Container describing a sinc-squared response

atten: numpy.ndarray

The attenuation of the response

freqs: numpy.ndarray

The frequencies the beam is evaluated at

fwhms: numpy.ndarray

The full-width at half-maximum corresponding to freqs

offset: float

Angular offset of the source

class flint.sky_model.SkyModel

Bases: NamedTuple

Description of the derived sky-model

apparent: bool = True

Whether the sources and model are absolute of apparent fluxes

calibrate_model: pathlib.Path | None = None

Path to the sky-model file created to use with calibrate

ds9_region: pathlib.Path | None = None

Path to the DS9 region file representing the sky-model

flux_jy: float

Total flux in Jansky

hyperdrive_model: pathlib.Path | None = None

Path to the sky-model file created to use with hyperdrive

no_sources: int

Number of source that are included in the sky-model

class flint.sky_model.SkyModelOptions(/, **data: Any)

Bases: flint.options.BaseOptions

Options that describe how to build a local sky-model, including where reference catalogues are stored, the preferred catalogue, the types of models to produce, and filtering criteria

assumed_alpha: float = -0.83

Assume this to be the typical spectral index if it is not recorded in the reference catalogue

assumed_q: float = 0.0

Assume this to be the typical amount of spectral curvature should they not be in the reference catalogue

flux_cutoff: float = 0.02

The intrinsic brightness a source needs to be for it to be included in the sky model

fwhm_scale_cutoff: float = 1

A source needs to be within this many FWHM units from the direction of interest for it to be included

reference_catalogue_directory: pathlib.Path

The reference catalogue directory that contains the known flint reference catalogues

reference_name: str | None = None

write_calibrate_model: bool = False

Should the model for calibrate be created. The output will have .calibrate.txt suffix appended to the MS path.

write_ds9_region: bool = False

Should a DS9 region file be created. The output will have .ds9.reg suffix appended to the MS path.

write_hyperdrive_model: bool = False

Should the model for hyperdrive be created. The output will have .hypderdrive.yaml suffix appended to the MS path.

class flint.sky_model.SkyModelOutputPaths

Bases: NamedTuple

Holds the expected names for different type of sky model outputs

calibrate_path: pathlib.Path

Path of the calibrate style sky catalogue

hyperdrive_path: pathlib.Path

Path of the hyperdrive style sky catalogue

region_path: pathlib.Path

Path of the ds9 region file

flint.sky_model._jinc(x)

flint.sky_model.cli() → None

flint.sky_model.create_sky_model(ms_path: pathlib.Path, sky_model_options: SkyModelOptions) → SkyModel | None

Create a sky-model to calibrate RACS based measurement sets.

If no sources were selected then None is returned.

Parameters:

• ms_path (Path) – Measurement set to create sky-model for

• sky_model_options (SkyModelOptions) – Options to use to construct the sky model

Returns:

SkyModel | None – Basic informattion concerning the sky-model derived and the output files. If no sources were selected then None is returned.

flint.sky_model.curved_power_law(nu: numpy.ndarray, norm: float, alpha: float, beta: float, ref_nu: float) → numpy.ndarray

A curved power law model.

>>> S_nu = S_nu_0 * (nu/nu_0)**alpha * exp(q*ln(nu/nu_0)**2.)

Note that in the case of q=0. the model reduces to a normal power-law.

Parameters:

• nu (np.ndarray) – Frequency array.

• norm (float) – Reference flux.

• alpha (float) – Spectral index.

• beta (float) – Spectral curvature.

• ref_nu (float) – Reference frequency.

Returns:

Model flux.

Return type:

np.ndarray

flint.sky_model.evaluate_src_model(freqs: astropy.units.Quantity, src_row: astropy.table.row.Row, ref_nu: astropy.units.Quantity) → astropy.units.Jy

Evaluate a SED of an object using its recordded Normalisation, alpha and q components.

Parameters:

• freqs (u.Quantity) – Frequencies to evaluate

• src_row (Row) – Source propertieis from which the parameters are extracted

• ref_nu (u.Quantity) – Reference frequency of the model parameterization

Returns:

Brightness of model evaluated across frequency

Return type:

u.Jy

flint.sky_model.fit_curved_pl(freqs: astropy.units.Quantity, flux: astropy.units.Quantity, ref_nu: astropy.units.Quantity) → CurvedPL

Fit some specified set of datapoints with a generic curved powerlaw. This is _not_ meant for real data, ratther as a way of representing the functional form of a model after it has been perturbed by some assumed primary beam.

Parameters:

• freqs (np.ndarray) – Frequencies corresponding to each brightness

• flux (np.ndarray) – Brightness corresponding to each frequency

• ref_nu (float) – Reference frequency that the model is set to

Returns:

The fitted parameter results

Return type:

CurvedPL

flint.sky_model.generate_airy_pb(freqs: astropy.units.Quantity, aperture: astropy.units.Quantity, offset: astropy.units.Quantity) → AiryResponse

Calculate the theoretical airy response of an aperture of a known size.

Parameters:

• reqs (u.Quantity) – Frequencies to evaluate the beam at

• aperture (u.Quantity) – Size of the dish

• offset (u.Quantity) – Offset from the centre of the beam

Returns:

Numerical results of the theoretical sinc-squared primary beam

Return type:

AiryResponse

flint.sky_model.generate_gaussian_pb(freqs: astropy.units.Quantity, aperture: astropy.units.Quantity, offset: astropy.units.Quantity) → GaussianResponse

Calculate the theoretical Gaussian taper for an aperture of known size

Parameters:

• freqs (u.Quantity) – Frequencies to evaluate the beam at

• aperture (u.Quantity) – Size of the dish

• offset (u.Quantity) – Offset from the centre of the beam

Returns:

Numerical results of the theoretical gaussian primary beam

Return type:

GaussianResponse

flint.sky_model.generate_pb(pb_type: str, freqs: astropy.units.Quantity, aperture: astropy.units.Quantity, offset: astropy.units.Quantity) → GaussianResponse | SincSquaredResponse | AiryResponse

Generate the primary beam response using a set of physical quantities. Each is assumed to be rotationally invariant, so a 1-D slice can be evaluated.

Known approximations are:

• gaussian

• sincsquared

• airy

Parameters:

• pb_type (str) – The type of approximation to use

• freqs (u.Quantity) – The frequency to valuate at.

• aperture (u.Quantity) – The size of the dish

• offset (u.Quantity) – The distance to measure out to

Raises:

ValueError – Raised if pb_type is not known

Returns:

Constructed primary beam responses

Return type:

Union[GaussianResponse, SincSquaredResponse, AiryResponse]

flint.sky_model.generate_sinc_squared_pb(freqs: astropy.units.Quantity, aperture: astropy.units.Quantity, offset: astropy.units.Quantity) → SincSquaredResponse

Calculate the theoretical sinc-squared response of an aperture of a known size.

See Equation 3.78 and 3.79 from: https://www.cv.nrao.edu/~sransom/web/Ch3.html

Parameters:

• reqs (u.Quantity) – Frequencies to evaluate the beam at

• aperture (u.Quantity) – Size of the dish

• offset (u.Quantity) – Offset from the centre of the beam

Returns:

Numerical results of the theoretical sinc-squared primary beam

Return type:

SincSquaredResponse

flint.sky_model.get_1934_model(mode: str = 'calibrate') → pathlib.Path

Construct the path to a 1934-638 model. This is intended to calibrate the bandpass.

Parameters:

mode (str, optional) – Calibration software intended to be used. This will determine model file to load. Supported modes are ‘calibrate’. Defaults to ‘calibrate’.

Raises:

ValueError – When supplied ‘mode’ is not known.

Returns:

Path to 1934-638 calibration model.

Return type:

Path

flint.sky_model.get_known_catalogue(cata: str) → flint.catalogue.Catalogue

Get the parameters of a known catalogue

TODO: Replace with configuration based method to load known cata

Parameters:

cata (str) – The lookup name of the catalogue

Returns:

properties of known catalogue

Return type:

Catalogue

flint.sky_model.get_parser()

flint.sky_model.get_sky_model_output_paths(ms_path: pathlib.Path) → SkyModelOutputPaths

Create a set of expected sky model output file paths

Parameters:

ms_path (Path) – The base name to construct the names against

Raises:

ValueError – If it appears ms_path does not point to a measurement set

Returns:

The set of paths to use when creating models

Return type:

SkyModelOutputPaths

flint.sky_model.load_catalogue(catalogue_dir: pathlib.Path, catalogue: str | None = None, ms_pointing: astropy.coordinates.SkyCoord | None = None, assumed_alpha: float = -0.83, assumed_q: float = 0.0) → tuple[flint.catalogue.Catalogue, astropy.table.Table]

Load in a catalogue table given a name or measurement set declinattion.

Parameters:

• catalogue_dir (Path) – Directory containing known catalogues

• catalogue (Optional[str], optional) – Catalogue name to look up from known catalogues. Defaults to None.

• ms_pointing (Optional[SkyCoord], optional) – Pointing direction of the measurement set. Defaults to None.

• assumed_alpha (float, optional) – The assumed spectral index to use if there is no spectral index column known in model catalogue. Defaults to -0.83.

• assumed_q (float, optional) – The assumed curvature to use if there is no curvature column known in model catalogue. Defaults to 0.0.

Raises:

FileNotFoundError – Raised when a catalogue can not be resolved.

Returns:

The Catalogue information and Table of components loaded

Return type:

Tuple[Catalogue,Table]

flint.sky_model.make_calibrate_model(out_path: pathlib.Path, sources: list[tuple[astropy.table.row.Row, CurvedPL]]) → pathlib.Path

Create a sky-model file that is compatible with the AO Calibrate software

Parameters:

• out_path (Path) – Output path of the model file

• sources (List[Tuple[Row,CurvedPL]]) – The sources and their (apparent) SED to write

Returns:

Output path of the model file

Return type:

Path

flint.sky_model.make_ds9_region(out_path: pathlib.Path, sources: list[astropy.table.row.Row]) → pathlib.Path

Create a DS9 region file of the sky-model derived

Parameters:

• out_path (Path) – Output path to of the region file to write

• sources (List[Row]) – Collection of Row objects (with normalised column names)

Returns:

Path to the region file created

Return type:

Path

flint.sky_model.make_hyperdrive_model(out_path: pathlib.Path, sources: list[tuple[astropy.table.row.Row, CurvedPL]]) → pathlib.Path

Writes a Hyperdrive sky-model to a yaml file.

Parameters:

• out_path (Path) – The output path that the sky-model would be written to

• sources (List[Tuple[Row,CurvedPL]]) – Collection of sources to write, including the

• SED (normalized row and the results of fitting to the estimated apparent)

Returns:

The path of the file created

Return type:

Path

flint.sky_model.preprocess_catalogue(cata_info: flint.catalogue.Catalogue, cata_tab: astropy.table.Table, ms_pointing: astropy.coordinates.SkyCoord, flux_cut: float = 0.02, radial_cut: astropy.units.deg = 1.0 * u.deg) → astropy.table.QTable

Apply the flux and separation cuts to a loaded table, and transform input column names to an expected set of column names.

Parameters:

• cata_info (Catalogue) – Description of the catalogue from known catalogues

• cata_tab (Table) – The loaded catalogue table

• ms_pointing (SkyCoord) – Pointing of the measurement set

• flux_cut (float, optional) – Flux cut in Jy. Defaults to 0.02.

• radial_cut (u.deg, optional) – Radial separation cut in deg. Defaults to 1..

Returns:

_description_

Return type:

QTable

flint.sky_model.KNOWN_1934_FILES

Known models of PKS B1934-638 in different formats

flint.sky_model.KNOWN_CATAS: dict[str, flint.catalogue.Catalogue]

Known sky-model catalogues that have had some pre-processing operations applied. Discuss with maintainers for access,

flint.sky_model.KNOWN_PB_TYPES = ('gaussian', 'sincsquared', 'airy')

flint.sky_model.NORM_COLS

Normalised column names and their corresponding astropy units.